pizzahut_stores

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations and no output schema, the description carries the full burden of behavioral disclosure, and it delivers. It reveals the unfiltered-call prohibition, the exact fields returned per restaurant (store number, full address with coordinates, phone, online-order acceptance, timezone), and the relationship to downstream endpoints. This exceeds what an agent could infer from the schema alone.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, no wasted words, and the essential information is front-loaded: what it searches, the required-filter constraint, and what results contain. Every sentence earns its place, and length is appropriate for an 11-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 11 parameters, no output schema, and no annotations, the description is unusually complete. It covers purpose, mandatory usage constraints, returned data fields, and downstream integration. The only minor omissions are pagination/sorting behavior, but max_results is already documented in the schema, leaving no critical gap for an agent to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds semantic value by enumerating which parameters act as filters and by warning that at least one is required. It also clarifies the store_number parameter's role as a bridge to other tools, which is not evident from the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Search Pizza Hut restaurants by city, state, postal code, name, franchise code, or store number.' It clearly identifies the tool as a plural store-search endpoint, distinct from the singular pizzahut_store and related menu/delivery tools. The redundant second sentence reinforces the filter scope without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states the mandatory condition 'At least one filter is required' and explains why unfiltered enumeration is intentionally disallowed. It also tells the agent that each returned store number is the value that /pizzahut/menu and /pizzahut/store consume, effectively routing the agent to downstream detail tools. However, it does not explicitly name an alternative tool to use instead, such as pizzahut_store for a single store's details.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.